Abstract
Mammogram images are important tools allowing visualization of various types of breast cancer. In fact, cancer detection refers to the extraction of region of interest ROI, which represents the tumor, in the mammogram image. In medical imaging field, Computer Aided Diagnosis systems (CAD) are used to analyze this type of images. To extract region of interest from mammograms, image segmentation methods have been wildly applied. These methods consist of partitioning the image on meaningful regions or segments easy to analyze. There are various techniques and methods of segmentation of mammogram images in the literature. In this paper, we present a survey of different approaches of segmentation that we compared theoretically in terms of advantages and drawbacks, particulary for mammogram images.
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Ait lbachir, I., Es-salhi, R., Daoudi, I., Tallal, S., Medromi, H. (2017). A Survey on Segmentation Techniques of Mammogram Images. In: El-Azouzi, R., Menasche, D.S., Sabir, E., De Pellegrini, F., Benjillali, M. (eds) Advances in Ubiquitous Networking 2. UNet 2016. Lecture Notes in Electrical Engineering, vol 397. Springer, Singapore. https://doi.org/10.1007/978-981-10-1627-1_43
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